Question

(Text Analysis) The availability of computers with string-manipulation capabilities has resulted in some rather interesting approaches to analyzing the writings of great authors. Much attention has been focused on whether William Shakespeare ever lived. Some scholars believe there is substantial evidence indicating that Christopher Marlowe actually penned the masterpieces attributed to Shakespeare. Researchers have used computers to find similarities in the writings of these two authors. This exercise examines three methods for analyzing texts with a computer. a) Write an application that reads a line of text from the keyboard and prints a table indicating the number of occurrences of each letter of the alphabet in the text. For example, the phrase To be, or not to be: that is the question: contains one “a,” two “b’s,” no “c’s,” and so on. b) Write an application that reads a line of text and prints a table indicating the number of one-letter words, two-letter words, three-letter words, and so on, appearing in the text. For example, Fig. 30.25 shows the counts for the phrase Whether 'tis nobler in the mind to suffer c) Write an application that reads a line of text and prints a table indicating the number of occurrences of each different word in the text. The first version of your application should include the words in the table in the same order in which they appear in the text. For example, the lines To be, or not to be: that is the question: Whether 'tis nobler in the mind to suffer contain the word “to” three times, the word “be” two times, the word “or” once, and so on. A more interesting (and useful) printout should then be attempted in which the words are sorted alphabetically.

Short answer

Use arrays/dictionaries to count occurrences of letters, word lengths, and words, adjusting for punctuation. Maintain insertion order for words initially, then sort alphabetically for the advanced output.

Step-by-step solution

Counting Letter Occurrences

To count the occurrences of each letter in the input text, initialize an array of size 26 to zero to represent each letter from 'a' to 'z'. Traverse through the input text, for each character, check if it's a letter. If it is, convert it to lowercase, calculate its position as an integer index using the formula: \[ \text{index} = \text{ord(lowercase ext{-}char)} - \text{ord('a')} \]increment the corresponding index in the array. Finally, print the count of each letter by iterating through the array.

Counting Words by Length

To count words of various lengths, split the text into words using spaces and punctuation as delimiters. Initialize a dictionary to store word lengths and their respective counts. For each word, determine its length (ignoring any punctuation at the end), and update the dictionary by incrementing the count of entry corresponding to that length. Print the sorted dictionary by length to display the results.

Counting Occurrences of Words

To count each word's occurrences while keeping track of their order, split the text into words, again using spaces and punctuation as delimiters. Use an ordered dictionary or list of tuples to maintain the order of first occurrences. Traverse each word; if it appears for the first time, add it to the ordered structure with a count of 1; if not, increment its count. Print the words and their counts maintaining the insertion order for the first version.

Alphabetical Order of Words

For the second version of word count, sort the words alphabetically after counting their occurrences. Use a standard dictionary for counting and then assign the dictionary's items to a list. Sort this list alphabetically by word. Finally, print the sorted list of words with their corresponding counts.

Key concepts

String Manipulation

String manipulation in text analysis involves modifying and analyzing strings to extract meaningful information. This process might include changing the string's characters, splitting the string into smaller pieces, or removing unwanted characters like punctuation.

Computers excel at string manipulation due to their ability to quickly evaluate and process text data. By properly manipulating strings, you can retrieve useful data about the text, such as letter and word frequency, and gain insights into the overall structure of a document.

Some common tasks in string manipulation:

• Changing case, like converting to lowercase or uppercase.
• Trimming unwanted spaces.
• Removing or substituting punctuation or special characters.
• Splitting strings into smaller parts, such as words or sentences.

These operations form the foundation for more complex analyses, enabling deep insights into the written content.

Letter Frequency

Letter frequency analysis helps in determining how often each letter of the alphabet appears in a given text. This is valuable in various applications, such as identifying an author's writing style or in cryptography tasks.

To conduct letter frequency analysis through coding, you begin by setting up an array with slots for each letter from 'a' to 'z'. As you process each character in a string, you verify whether it is a letter and convert it to lowercase to treat 'A' and 'a' equally.

The letter’s position can be calculated using a formula: \[ \text{index} = \text{ord(lowercase\_char)} - \text{ord('a')} \] Once you determine the position, you increment the corresponding array index, which altogether builds up a complete picture of the letter distribution in the text.

This method provides a snapshot of how letters are utilized in the text and may reveal unique characteristics of a writing sample, such as frequent usage of specific letters.

Word Length Counting

Word length counting aims to measure how many times words of various lengths appear within a text. This can help understand the complexity and style of the writing, giving insights into the author's choice of language.

To perform this in a practical setting, you split the text into separate words using spaces or punctuation as boundaries. Make sure to filter out punctuation at the end of words to get accurate word lengths.

As you go through each word, record its length and update a dictionary containing word lengths and their frequencies. This dictionary helps in organizing words by their length, showing which lengths are most prevalent in the text.

Finally, printing this dictionary sorted by length gives a structured view of the content's complexity. Longer words may indicate a more formal or complex writing style, while shorter words suggest simplicity or possibly a focus on clarity.

Word Frequency Analysis

Word frequency analysis reveals how often words appear in a text, providing insights into the topics or themes emphasized by the author. This analysis starts by splitting the text into words, accounting for spaces and punctuation.

Use data structures like ordered dictionaries or lists of tuples to maintain order if the sequence of words is important. Initially, for each new word encountered, it is added to the structure with a count of one. Encountering the same word again increments the existing count.

This gives a basic view of the text's word usage. For deeper analysis, sorting the words alphabetically after counting can enhance readability and comparisons, showcasing word relevance and frequency.

Word frequency analysis is often used in content analysis, linguistic studies, and SEO practices, providing a clear picture of important subjects or unique features in written work.